Here, we will perform patient- and time-point-specific clustering. If we can indeed predict Richter-like cells at the early stages of the disease, then they should cluster together without having the Richter time-point present. On the other hand, if they were poor-quality cells, then they might scatter everywhere in the absence of a Richter-like cluster.
library(Seurat)
library(tidyverse)
path_to_obj <- here::here("results/R_objects/patient_63/7.seurat_list_annotated_reprocessed.rds")
# Colors
color_palette <- c("black", "gray", "red", "yellow", "violet", "green4",
"blue", "mediumorchid2", "coral2", "blueviolet",
"indianred4", "deepskyblue1", "dimgray", "deeppink1",
"green", "lightgray", "hotpink1")
# Source functions
source(here::here("bin/utils.R"))
seurat_list <- readRDS(path_to_obj)
seurat_12 <- seurat_list$`12`
seurat_list_12 <- SplitObject(seurat_12, split.by = "time_point")
seurat_list_12 <- seurat_list_12[sort(unique(seurat_12$time_point))]
seurat_list_12 <- purrr::map(seurat_list_12, process_seurat, dims = 1:20)
umaps_time_points_12 <- purrr::map(
seurat_list_12,
DimPlot,
pt.size = 0.8,
cols = color_palette
)
umaps_time_points_12
## $T1
##
## $T2
##
## $T4
##
## $T5
##
## $T6
seurat_19 <- seurat_list$`19`
seurat_list_19 <- SplitObject(seurat_19, split.by = "time_point")
seurat_list_19 <- seurat_list_19[sort(unique(seurat_19$time_point))]
seurat_list_19 <- purrr::map(seurat_list_19, process_seurat, dims = 1:20)
umaps_time_points_19 <- purrr::map(
seurat_list_19,
DimPlot,
pt.size = 0.8,
cols = color_palette
)
umaps_time_points_19
## $T1
##
## $T3
##
## $T4
##
## $T5
##
## $T6
seurat_3299 <- seurat_list$`3299`
seurat_list_3299 <- SplitObject(seurat_3299, split.by = "time_point")
seurat_list_3299 <- seurat_list_3299[sort(unique(seurat_3299$time_point))]
seurat_list_3299 <- purrr::map(seurat_list_3299, process_seurat, dims = 1:20)
umaps_time_points_3299 <- purrr::map(
seurat_list_3299,
DimPlot,
pt.size = 0.8,
cols = color_palette
)
umaps_time_points_3299
## $T1
##
## $T2
##
## $T3
sessionInfo()
## R version 4.0.4 (2021-02-15)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.2 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=es_ES.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=es_ES.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=es_ES.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=es_ES.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] forcats_0.5.1 stringr_1.4.0 dplyr_1.0.6 purrr_0.3.4 readr_1.4.0 tidyr_1.1.3 tibble_3.1.2 ggplot2_3.3.3 tidyverse_1.3.0 SeuratObject_4.0.1 Seurat_4.0.1 BiocStyle_2.18.1
##
## loaded via a namespace (and not attached):
## [1] readxl_1.3.1 backports_1.2.1 plyr_1.8.6 igraph_1.2.6 lazyeval_0.2.2 splines_4.0.4 listenv_0.8.0 scattermore_0.7 digest_0.6.27 htmltools_0.5.1.1 fansi_0.4.2 magrittr_2.0.1 tensor_1.5 cluster_2.1.1 ROCR_1.0-11 globals_0.14.0 modelr_0.1.8 matrixStats_0.58.0 spatstat.sparse_2.0-0 colorspace_2.0-1 rvest_1.0.0 ggrepel_0.9.1 haven_2.3.1 xfun_0.22 crayon_1.4.1 jsonlite_1.7.2 spatstat.data_2.1-0 survival_3.2-10 zoo_1.8-9 glue_1.4.2 polyclip_1.10-0 gtable_0.3.0 leiden_0.3.7 future.apply_1.7.0 abind_1.4-5 scales_1.1.1 DBI_1.1.1 miniUI_0.1.1.1 Rcpp_1.0.6 viridisLite_0.4.0 xtable_1.8-4 reticulate_1.20 spatstat.core_2.1-2 htmlwidgets_1.5.3 httr_1.4.2 RColorBrewer_1.1-2 ellipsis_0.3.2 ica_1.0-2 farver_2.1.0 pkgconfig_2.0.3 sass_0.4.0 uwot_0.1.10 dbplyr_2.1.0 deldir_0.2-10
## [55] utf8_1.2.1 here_1.0.1 tidyselect_1.1.1 labeling_0.4.2 rlang_0.4.11 reshape2_1.4.4 later_1.2.0 munsell_0.5.0 cellranger_1.1.0 tools_4.0.4 cli_2.5.0 generics_0.1.0 broom_0.7.5 ggridges_0.5.3 evaluate_0.14 fastmap_1.1.0 yaml_2.2.1 goftest_1.2-2 knitr_1.31 fs_1.5.0 fitdistrplus_1.1-3 RANN_2.6.1 pbapply_1.4-3 future_1.21.0 nlme_3.1-152 mime_0.10 xml2_1.3.2 compiler_4.0.4 rstudioapi_0.13 plotly_4.9.3 png_0.1-7 spatstat.utils_2.1-0 reprex_1.0.0 bslib_0.2.5 stringi_1.6.2 highr_0.8 RSpectra_0.16-0 lattice_0.20-41 Matrix_1.3-3 vctrs_0.3.8 pillar_1.6.1 lifecycle_1.0.0 BiocManager_1.30.10 spatstat.geom_2.1-0 lmtest_0.9-38 jquerylib_0.1.4 RcppAnnoy_0.0.18 data.table_1.14.0 cowplot_1.1.1 irlba_2.3.3 httpuv_1.6.1 patchwork_1.1.1 R6_2.5.0 bookdown_0.21
## [109] promises_1.2.0.1 KernSmooth_2.23-18 gridExtra_2.3 parallelly_1.25.0 codetools_0.2-18 MASS_7.3-53.1 assertthat_0.2.1 rprojroot_2.0.2 withr_2.4.2 sctransform_0.3.2 mgcv_1.8-34 parallel_4.0.4 hms_1.0.0 grid_4.0.4 rpart_4.1-15 rmarkdown_2.7 Rtsne_0.15 shiny_1.6.0 lubridate_1.7.10